Cambridge Analytica has denied any wrongdoing and said that the business tactics it used are widespread among other firms.

But a day after the scandal hit, Facebook’s shares plummeted on Wall Street amid a privacy backlash. The worry is the incident could also affect legitimate academic research.

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Implications

Social media data is a rich source of information for many areas of research in psychology, technology, business and humanities. Some recent examples include using Facebook to predict riots, comparing the use of Facebook with body image concern in adolescent girls and investigating whether Facebook can lower levels of stress responses, with research suggesting that it may enhance and undermine psychosocial constructs related to well-being.

Universities, research organisations and funders govern the integrity of research with clear and strict ethics procedures designed to protect participants in studies, such as those in which social media data is used. The harvesting of data without permission from users is considered an unethical activity under commonly understood research standards.

The fallout from the Cambridge Analytica controversy is potentially huge for researchers who rely on social networks for their studies, where data is routinely shared with them for research purposes. Tech companies could become more reluctant to share data with researchers. Facebook is already extremely protective of its data – the worry is that it could become doubly difficult for researchers to legitimately access this information in light of what has happened.

Data analytics

Clearly, it’s not just researchers who use profile data to better understand people’s behavioural patterns. Marketing organisations have been profiling consumers for decades – if they know their customers, they will understand the triggers that prompt a purchase of their product, enabling them to adjust marketing messages to improve sales. It has become easier with digital marketing – people are constantly tracked online, their activities are analysed using data analytics tools and personal recommendations are made. Such methods are core to the business strategies of tech giants’ such as Amazon and Netflix.

Information from online behaviour can be used to predict people’s mood, emotions and personality. My own research into Intelligent Tutoring Systems uses learner interactions with software to profile personality type so it can automatically adapt tutoring to someone’s preferred style. Machine learning techniques can combine theories from psychology with new patterns found – such as Facebook “likes” – to profile users.

Eli Pariser, who is the CEO of viral content website Upworthy, has been arguing against personalisation tools since 2011. He has warned against the dangers of information filtering, and believes that the use of algorithms to profile people to show them information tailored to personal tastes is bad for democracy.

While these fears appear to be borne out by some allegations levelled against Cambridge Analytica, it’s worth noting that there has been no evidence to show that the company’s use of its psychometric tool in Donald Trump’s campaign saw US votes swung in his favour.

However, collateral damage is possible, not least because researchers might find it more difficult to get Facebook – and its users – to agree to hand over the data for research alone.